Sun Tong, Zeng Xin, Hao Peng Hui, Chin Chien Ting, Chen Mian, Yan Jie Jie, Dai Ming, Lin Hao Ming, Chen Siping, Chen Xin
School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518060, China.
Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China.
Math Biosci Eng. 2020 Mar 30;17(4):2864-2880. doi: 10.3934/mbe.2020161.
Magneto-Acousto-Electrical Tomography (MAET) is a novel multi-physics imaging method, which promises to offer a unique biophysical property of tissue electrical impedance with the additional benefit of excellent spatial resolution of the ultrasonic imaging. It opens the potential for early diagnosis of cancer by revealing changes of dielectric characteristics. However, direct MAET is unable to image the irregularly-shaped lesions fully due to the dependence on the angle between conductivity boundary and ultrasound beam direction. In this paper, a numerical simulation of multi-angle MAET is presented for an improved image reconstruction for MAET in order to discern irregularly-shaped tumors in different positions. The results show that the conductivity boundary interfaces are invisible in single angle B-mode reconstructed image, wherever the ultrasound beam and conductivity boundary are nearly parallel. When the multi-angle scanning was adopted, the image reconstructed with image rotation method reproduced the original object pattern. Furthermore, the relationship between reconstruction error and the number of angles was also discussed. It is found that 12 angles would be necessary to achieve nearly the optimal reconstruction. Finally, reconstructed images in norm of the error with the measurement noise are presented.
磁声电层析成像（MAET）是一种新型的多物理场成像方法，有望提供组织电阻抗独特的生物物理特性，同时具备超声成像出色的空间分辨率这一额外优势。它通过揭示介电特性的变化，为癌症的早期诊断开辟了潜力。然而，由于依赖于电导率边界与超声束方向之间的夹角，直接的MAET无法完整地对形状不规则的病变进行成像。本文提出了多角度MAET的数值模拟，以改进MAET的图像重建，从而辨别不同位置的形状不规则的肿瘤。结果表明，在单角度B模式重建图像中，无论超声束与电导率边界是否近乎平行，电导率边界界面都是不可见的。当采用多角度扫描时，用图像旋转方法重建的图像再现了原始物体图案。此外，还讨论了重建误差与角度数量之间的关系。发现需要12个角度才能实现近乎最优的重建。最后，给出了存在测量噪声情况下误差范数的重建图像。
